Selecting a variant of forest regeneration cuttings that would ensure fulfilling multiple, frequently conflicting forest functions is a challenging task for forest management planning. The aim of this work is to present an efficient and complex analysis of the impact of different forest management scenarios on stand wind stability, timber production (economy), and biodiversity of a secondary mixed temperate forest in Central Europe. We evaluated four different harvest-regeneration systems: clear-cutting, shelter-wood, selection cutting, and no-cutting using theSIBYLA growth simulator. We simulated forest stand development over time and applied 450 variants of 4 harvest-regeneration systems. The selected outputs from the simulator were used as indicators of the fulfilment of wood-production and non-wood-production functions. The calculated indicators were forest stability (height/diameter ratio), economic efficiency (soil expectation value, SEV), and tree species diversity (Shannon index). These indicators were used as inputs for multi-criteria a posteriori decision analysis using the weighted summation method and Pareto fronts. The results revealed substantial trade-offs among the three investigated criteria. The decision space was highly sensitive to their weighting system and included all regeneration systems. The Pareto fronts for wind stability revealed that the maximum stability could be achieved with shelter-wood based on target diameter. This variant, however, fulfils the other two examined functions only to a limited extent (SEV and diversity only to 9% and 27% of their absolute maxima). Other similar variants achieve high stability by sacrificing the diversity and increasing SEV, simultaneously. If a high diversity level is favoured, optimal stability could be achieved by the selection system. The proposed approach enables objective testing of a large number of variants, and an objective assessment of stand management planning since it provides us with the complex multi-dimensional picture about the impact of criteria weights on the selection of optimal variants, and the relative fulfilment of individual criteria.
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